IMPACT OF GLOBALIZATION ON POVERTY IN PAKISTAN

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DOI: https://orcid.org/0000-0001-5767-6229

IMPACT OF GLOBALIZATION ON POVERTY IN PAKISTAN

Afroz Umair¹, Prof. Dr. Abdul Ghafoor Awan²

ABSTRACT-The main objective of this research paper is to measure the impact of globalization on poverty in Pakistan. Poverty is world biggest curse in the past and present and different organization and institutions of the world are trying to eradicate it from the world. Globalization and poverty related in world and also in Pakistan.

This study examines the impact of globalization on poverty in Pakistan. We used secondary data because it is more reliable and applied the ARDL approach to draw empirical results which reveal that trade openness, foreign direct investment and gross domestic product have negative relations with poverty while population and external debt has positive relationship with poverty. This study recommends that using globalization as a tool and making such policies that especially for the poor’s will help government to eliminate poverty from Pakistan.

Key Words. Globalization, poverty, trade openness, FDI, GDP, external debt.

Type of study: Original Research paper Paper received: 02.07.2019

Paper accepted: 15.08.2019 Online published: 01.10.2019

__________________________________________________________________

1. M.Phil Scholar, Department of Economics, Institute of Southern Punjab.

umairbhutta90@gmail.com. Cell # +

2. Dean, Faculty of Management and Social Sciences, Institute of Southern Punjab.

ghafoor70@yahoo.com. Cell # +0923136015051.

1.INTRODUCTION:

1.1. Background of study:

Globalization, by definition, is the integration and democratization of the world’s culture, economy, and infrastructure through transnational investment, rapid proliferation of communication and information technologies, and the impacts of free-market on local, regional and national economies. Globalization is made the world globalize and link to each other with ease. Globalization made the world to a global village. Globalization has changed the development of many countries like as an example of China, Singapore, Malaysia, Indonesia and so on. Economically globalization in modern era is a leading factor enhancing the production function, improving the quality of components, spinning the services to trade liberalization and also globalization increasing the peace by his globalizing policies learning from the examples of past. Globalization has significant effect on culture, economic development, social, peace and prosperity in the world, well-being of human social societies and also on highly impact on environment all over the world

Although globalization term is new but from the beginning of the world people are cooperating with each other in a different shapes of trade like barter system in which they exchange goods with goods or goods with services, they travelled from one part of the world to another part of the world for business, such as example of famous silk road of Pakistan that connects central Asia to Europe and China. After becoming the world globalized people are now investing in real state enterprises and also trying to get benefit to the third world countries like Burma, Ethiopia, Uganda which are facing some serious issues of economy, lack of education, malnutrition.

This current wave of Globalization has opened every country economy for the world internationally and domestically also. After the world war world people feel that there should be a autonomous body that should play a role in reducing conflicts between countries in the world. In this sense United Nations organization came in to being in 1945 for peace making and other basic necessities of life such providing education to whole world working for the rights of societies in the world and so many other factors

that affecting the people like poverty in many countries of the world. Much economic organization like GATT, SAARC and Europe Union are working for free trade. Many governments have adopted trade liberalization to accelerate economic pace. Many countries rapidly increasing their production, workers’ skills, potential and innovating new ways of opportunities of enhancing their capital market and investment in the world learning from the example of developed countries. Many organizations like GATT, SAARC, IMF, European Union and WTO are working on trade liberalization and negotiated dramatic reduction in quotas tariff trade barriers and have settled agreement to enhance free trade of services, promote goods and investment. Learning from the developed nations and making new foreign partnership and taking advantage in developing new opportunities of economic development.

Globalization is multifaceted concept of modern era and it includes political elements social cultural and also globalizing the world through communication. Poverty is assumed as a world biggest curse, it is deep rooted and almost it is dramatically related to inequality of resources and opportunities. As a vast concept of globalization, poverty is also changing its conditions and adapting according to social political and dynamic sanded chronological changes. Poverty has two types’ absolute poverty and relative poverty. Absolute poverty indicates the basic facilities of life like health food clothing shelter and sanitation while relative poverty refers to income inequality in a society or location from region to region where they live. Many organizations and united nations has the premier goal is to eradicate all forms of poverty from the world and in this regard they are working on different programmed. World Bank and United Nations has estimated that 1/5 population were facing shortage of basic facilities of (World Bank 2008 report). After 1980 unemployment rate in Pakistan is increasing and almost 7.5% of population facing financial problems due to lack of opportunities of work. Pakistan GDP rate is also not stable and it almost staggering from 3% to 4%

of GDP during three decades. While external debt of Pakistan is also increasing day by day. Growing population also a big issue in Pakistan. Pakistan is still lie in that list which is mostly populated countries of the world and Pakistan population is doubled

from 1981 census to 2017 conducted by the Government. An even last fifty years Population control programmer country to another country and not a single country of the world is saved from this curse.

1.2 Research Question:

Poverty is itself a curse and it has negative impact on development of any country like Pakistan. The main objective of this study is to study the impact of globalization on Pakistan’s Economy and particularly on poverty.

1.3 Objective of the study:

The main objectives of study are stated as under:-

1. To find out the impact of globalization on poverty in Pakistan during last five decades from1972 to 2017.

2. To study the impact of trade liberalization on poverty in Pakistan.

3. To examine the issue of poverty in Pakistan.

4. To examine the globalization effects on poverty alleviation.

5. To suggest measures how to reduce poverty.

2. LITERATURE REVIEW:

The primary and foremost aim of this study is to reviewing the existing literature is make clear sense about the empirical and theoretical work done by the different researchers in the past and present investigations on this topic and keeping eye on existing gap in previous research. Literature review assists researchers in formulating conceptual framework and data methodology.

Awan (2016) emphasized that globalization has benefited the developing countries in many ways. It provided the opportunity to avail the new technology and new invention produced by the developed countries. It enables the business organization of developing countries to be competitive. Capital moved from developed to developing countries while labor moved to developing countries to developed countries.

Awan (2012) said that globalization has brought many benefits in the shape of transfer of technology, goods and services, reducing transportation cost and

enhancing mobility of goods and labour from one country to another. But it caused poverty in those countries which could not compete in the world market and are producing primary goods.

Faridi and Chaudhary (2013) examined the impact of globalization and its effect on poverty in Pakistan. They used secondary data of Pakistan from year (1972 to 2010). The imposed the technique of Johnson co integration to measure short run and also long run relationship between variables. They choose FDI, Liberalization of trade, capital flows, technology and immigration as variables of the study. Finally, they reached the result that globalization has positive effect on the significance of employment generation. They recommended that for the enhancement in employment in employment. Free trade is compulsory for the specialization in new fields of economics.

Cheema and Sial (2012) measured income inequality, poverty and Growth link in Pakistan. They used secondary data eight different surveys of Household and expenditure conducted 1992-93 to 2007-08 in Pakistan. They used head count ratio to measure the poverty. In order to obtain poverty and growth they used Calorie based Approach that used expenditure as a welfare indicator for poverty line. While in this research paper they used household, expenditure income, size of household, food consumption, rural and urban area, electricity, education and poverty as variable of the study. They observed that economic growth is helpful in raising the per capita income. They also observed that income inequality can be minimize and beneficial for poor. They also observed that if growth causes income inequality than poverty will rise sharply. They calculated that income inequality and growth has significant link. They also calculated that electricity usage is more than in urban areas rather than in rural areas. They suggested that using growth economy Pakistan can overcome income inequality between provinces.

Shahnawaz et.al (2010) analyzed the globalization effects on employment evidence of Pakistan. The data they picked to use here was time series data from year (1973 to 20009). The techniques they used here was Johnson co integration and error

correction approach for short run analysis and Johnson co integration technique. They used secondary data. The variables they selected here to define the globalization on employment is workers’ remittances, trade openness, foreign direct investment, spread of technology and GDP. They found the result that showed us worker remittances, foreign direct investment and economic dimensions of globalization has major effect on employment opportunities creation not in long run but also in short run period. On the other hand, trade openness, political and social aspect of globalization has inverse effects on employment. Reason behind in this case is some internal and external imbalances in Pakistan.

Hameed and Nazir (2009) studied to examine the effects of economic globalization on poverty and equality. They used secondary data of Pakistan Economic survey from 1970-2004 and applied vector error correction model (VECM) and granger causality point estimation to find the results of the study. They took poverty, unemployment rate, trade liberalization, gross domestic product and per capita income as variables of the study. They observed that globalization is much helpful in the resource utilization, change the life standard and also has positive impact on economic development of the economy but increase the level of poverty.

They recommended that policies should be made for the improvement of poor people and also invest in such sectors that increase the opportunities of jobs.

Okumbowa, et (2010) investigated the effect of globalization and rate of poverty in Nigeria. In this regard they used the secondary data from year (1981 to 2009). They levied the technique of error correction approach and co integration model to measure the globalization effect on poverty in Nigeria. They picked these variables to measure the globalization which is this foreign direct investment.

Domestic investment, trade openness technology and import and export of the country. By using time series, they found the result that trade openness has positive impact on Nigerian economy in reducing poverty while on the other hand they found that foreign direct investment has inverse impact on the Nigerian economy. The result of the study high lightened the suggestion of some policies which can increase the

sustainable industrial development growth in return of reducing the poverty, in the end Globalization can reduce poverty if we focus on industrial sector and boost up with positive policies.

Sirinivasan and Bhagwati (2002) reveal that if a country wanted to enjoy high growth rate than he should follow export led development policies and relies on free trade. Country must focus on macroeconomics policies, strategies and stability.

Because low inflation is a channel that affects the poor positively and high inflation also hit the poverty very badly.

Ventura and Acemoglu (2002) provided another theoretical evidence to support the theory of trade openness leads to stabilize the world. Even in the absence of diminishing return in production and technological pullover. The reason behind is that diminishing return to scale and specialization introduced a new world of economic growth. Rapidly increasing globalization and new agreement among countries are boosting the competitions and establishing the new industries and markets in the world

3. RESEARCH METHODOLOY:

3.1 Type of data:

We have used time series data from 1972-2017 to answer the impact of globalization on poverty in Pakistan in the context of trade openness, FDI, GDP, external debt and inflation to measure the globalization impact on poverty in Pakistan.

3.2 Model Description:

we assume that globalization has its impact on poverty of Pakistan and we determined it with trade, GDP and remittances. In this study we will examine the impact of globalization on poverty in the context of Pakistan. We will use ARDL technique will be used to check the impact of globalization on poverty in Pakistan.

We developed the following model for empirical analysis of our study: - POV = f (TRDO, FDI, GDPA, XDBT, GPA, INF) POV = Headcount measure of poverty

TRDO = Trade openness

FDI = Foreign direct investment

GDPA = Gross Domestic Product %Annual XDBT = External Debt

GPA = Gross Population Annual % INF = Inflation

This model can be written in equation form as under:

𝐏𝐎𝐕 = 𝛃𝟎 + 𝛃𝟏𝐓𝐑𝐃𝐎 + 𝛃𝟐𝐅𝐃𝐈 + 𝛃𝟑𝐔𝐆𝐏𝐚 + 𝛃𝟒𝐆𝐃𝐏𝐚 + 𝛃𝟓𝐗𝐃𝐁𝐓 + 𝛃𝟔𝐈𝐍𝐅 + 𝛍𝐢

Where POV = poverty, βo = intercept, µi= error term of the model and

β1, β2, β3, β4, β5, β6 𝛽7𝛽8 are the coefficient of trade openness, foreign direct investment, unemployment rate, GDP annual growth rate, external debt, inflation and gross population annual percentage use respectively.

3.3. Selected Variables:

The selected variables and their definitions are shown in Table 1:

Table 1: Variable and their description

Variable Definitions Source

PHCR

Aggregate incidence of Poverty (Head Count Ratio in terms of percent)

Malik (1998). Amjad and Kemal (1997). Jamal(2005) and different Economic Survey Of Pakistan and census of 2017

FDIGDP

Foreign Direct Investment net flow as % of Gross Domestic Product

World Bank , world development indicator (WDI) 2011

EXTGNI External Debt % of Gross National Income

International Monetary Fund (IMF)

PGA Population Growth Annual % World Bank, world development Indicator(WDI) 2011

RTOP Trade openness calculated the sum of Ratio of import and export to GDP

World Bank, world Development Indicator(WDI) constant 2011 US Dollars

INF Consumer Price index as a measure of Inflation

Economic Survey Of Pakistan consumer Annual % of 2011 US Dollars

GDPA Gross Domestic Product (Annual %)

Bureau of Statistics, Govt of Pakistan

3.5 Analytical Technique:

We will use Ordinary Least Square method to draw the results.

4. DATA ANALYSIS:

4.1 Descriptive statistics:

We have described the variables and their prior expected signs in table 2:

Table 2: Descriptive statistics

Variable Descriptions A Prior Expectations

POV Headcount Measure of Poverty -

TRDO Trade Openness +

FDI Foreign Direct Investment +

GDPA GDP Annual +

XDBT External Debt -

INF Inflation +

GPA Gross Population Annual +

µ Stochastic Term

4.2 Stationarity of Variable and Unit Root test:

In time series data to check the variable is stationary or not we have to use the Augmented Dickey Fuller test to estimate the unit root of all the variables. ADF have employed on level and 1^st difference with intercept and trend and intercept. The results are described in the giving table below 3.

Table 2: Result of Augmented Dickey Fuller (ADF) Test Unit Root Test Variable Level

intercept

Level trend

&intercept

1^st difference intercept

1^st difference trend

intercept

GDPA 0.0001 0.0001 0.0000 0.0000

FDIGDP 0.0480 0.0658 0.0001 0.0007

EXTGNI 0.4876 0.2557 0.0000 0.0000

PGA 0.9750 0.1576 0.0010 0.0052

RTOP 0.0984 0.0305 0.0000 0.0000

INFLATION 0.0216 0.0872 0.0000 0.0004 Source: Author’s estimations using E-Views software

The data in table 3 show that all variable is stationary at 1st difference intercept while one variable is stationary on level intercept. We found that all variables are stationary on 1^st difference intercept except the gross domestic product

% per annual which is stationary on level 1 intercept.

4.3 ARDL Bound test results:

We used hare Auto regressive distributed lag model to find out the globalization impact on poverty in Pakistan because the entire variable is not stationary on level intercept. After employing the technique of autoregressive lag model we found the short run result of ARDL of this model. For this purpose, we used bound test. The results are shown in Table 4:

Table 4 ARDL Bound Test results ARDL Bounds Test

Date: 03/25/19 Time: 14:50 Sample: 1976 2017

Included observations: 42

Null Hypothesis: No long-run relationships exist

Test Statistic Value K

F-statistic 5.020215 6

Critical Value Bounds

Significance I0 Bound I1 Bound

10% 2.12 3.23

5% 2.45 3.61

2.5% 2.75 3.99

1% 3.15 4.43

4.4.OLS Model Results:

Table 5: Results of OLS Method Dependent Variable: D(PHCR)

Method: Least Squares Date: 03/25/19 Time: 14:50 Sample: 1976 2017

Included observations: 42

Variable Coefficient Std. Error t-Statistic Prob.

D(PHCR(-1)) 0.325436 0.158352 2.055147 0.0789

D(PHCR(-2)) 0.428450 0.156075 2.745154 0.0287

D(PHCR(-3)) 0.267811 0.210606 1.271619 0.2441

D(GDPA) 0.753388 0.367985 2.047335 0.0798

D(GDPA(-1)) 1.544686 0.774254 1.995064 0.0862

D(GDPA(-2)) 1.773542 0.556374 3.187676 0.0153

D(GDPA(-3)) 0.469521 0.302759 1.550809 0.1649

D(EXTGNI) -0.394766 0.256315 -1.540159 0.1674

D(EXTGNI(-1)) 0.525595 0.253972 2.069496 0.0773

D(EXTGNI(-2)) -1.151764 0.317112 -3.632045 0.0084

D(EXTGNI(-3)) 0.153331 0.113150 1.355116 0.2175

D(FDIGDP) 2.646857 1.675125 1.580095 0.1581

D(FDIGDP(-1)) -7.807967 2.807264 -2.781344 0.0272 D(FDIGDP(-2)) -0.950745 1.923275 -0.494337 0.6362 D(FDIGDP(-3)) -5.553005 2.369194 -2.343838 0.0516

D(PGA) 50.81263 19.64580 2.586438 0.0361

D(PGA(-1)) -30.99681 15.67185 -1.977866 0.0885

D(PGA(-2)) 73.70790 14.61766 5.042388 0.0015

D(PGA(-3)) -10.03542 10.76996 -0.931798 0.3825

D(RTOP) -33.98151 15.67499 -2.167881 0.0668

D(RTOP(-1)) 113.2407 45.56760 2.485114 0.0419

D(RTOP(-2)) 86.71421 35.03408 2.475139 0.0425

D(RTOP(-3)) 16.21542 21.12243 0.767687 0.4678

D(INFLATION) 0.356444 0.135140 2.637597 0.0335

D(INFLATION(-1)) -0.408591 0.166597 -2.452579 0.0439 D(INFLATION(-2)) -0.345997 0.142983 -2.419849 0.0461 D(INFLATION(-3)) 0.480229 0.146283 3.282870 0.0134

C 18.51181 10.43635 1.773782 0.1194

GDPA(-1) -0.650215 1.002217 -0.648777 0.5372

EXTGNI(-1) 0.501991 0.146400 3.428905 0.0110

FDIGDP(-1) 11.65178 4.413587 2.639980 0.0334

PGA(-1) 18.25601 9.909561 1.842262 0.1080

RTOP(-1) -202.9154 76.05802 -2.667903 0.0321

INFLATION(-1) 0.656433 0.203954 3.218537 0.0147

PHCR(-1) -1.051122 0.236316 -4.447940 0.0030

R-squared 0.951996 Mean dependent var -0.248571

Adjusted R-squared 0.718832 S.D. dependent var 2.904459 S.E. of regression 1.540097 Akaike info criterion 3.576475 Sum squared resid 16.60329 Schwarz criterion 5.024533 Log likelihood -40.10597 Hannan-Quinn criter. 4.107245

F-statistic 4.082952 Durbin-Watson stat 3.060026

Prob(F-statistic) 0.029576

Source: Author’s estimations using E-Views software

If the value of F statistics is lower than the bound test that it entails no integration but we found here the value of F statistics value of K is greater than the value of bound test on critical value of 10% , 5%, 2.5% and also greater than the value of !%. Its means we reject the null hypothesis and there is no short run relationship, so bound test conclude that there is long run relationship between the variable. The value of F statistics is greater than the value of efficiency on 10% of 0bound test 2.120 and also greater than on 1 level of bound test value 3.3. while on 5% of efficiency the value of F statistics is also > than the value of 0 bound test 2.45 and on 1level of bound test the value is 3.61 is less than the value of F statistics 5.020215 similarly the value of F statistics is also greater than the 2.5% efficiency value of 0 bound and 1 bound level and also greater than the 1% efficiency. As we know poverty is a big curse in the world and we cannot eradicate poverty from the world without making long term policies.

4.5 ARDL Model results:

Now we would like to show the result of Autoregressive distributed lag model to check co-integration.

Table 6: Long run relationship ARDL Co integrating And Long Run Form

Dependent Variable: PHCR

Selected Model: ARDL(4, 4, 4, 4, 4, 4, 4) Date: 03/25/19 Time: 14:49

Sample: 1972 2017 Included observations: 42

Co integrating Form

Variable Coefficient Std. Error t-Statistic Prob.

D(PHCR(-1)) 0.325436 0.158352 2.055147 0.0789 D(PHCR(-2)) 0.428450 0.156075 2.745154 0.0287 D(PHCR(-3)) 0.267811 0.210606 1.271619 0.2441

D(GDPA) 0.753388 0.367985 2.047335 0.0798

D(GDPA(-1)) -0.228855 0.352333 -0.649542 0.5367 D(GDPA(-2)) 1.304021 0.397398 3.281393 0.0135 D(GDPA(-3)) 0.469521 0.302759 1.550809 0.1649 D(EXTGNI) -0.394766 0.256315 -1.540159 0.1674 D(EXTGNI(-1)) 1.677359 0.419260 4.000765 0.0052 D(EXTGNI(-2)) -1.305095 0.327906 -3.980091 0.0053 D(EXTGNI(-3)) 0.153331 0.113150 1.355116 0.2175 D(FDIGDP) 2.646857 1.675125 1.580095 0.1581 D(FDIGDP(-1)) -6.857222 2.852844 -2.403644 0.0472 D(FDIGDP(-2)) 4.602260 2.230041 2.063756 0.0779

D(FDIGDP(-3)) -5.553005 2.369194 -2.343838 0.0516

D(PGA) 50.812632 19.645797 2.586438 0.0361

D(PGA(-1))

-

104.704715 27.026222 -3.874190 0.0061 D(PGA(-2)) 83.743327 19.124921 4.378754 0.0032 D(PGA(-3)) -10.035424 10.769957 -0.931798 0.3825 D(RTOP) -33.981510 15.674989 -2.167881 0.0668 D(RTOP(-1)) 26.526462 19.565435 1.355782 0.2173 D(RTOP(-2)) 70.498797 32.127546 2.194341 0.0643 D(RTOP(-3)) 16.215417 21.122433 0.767687 0.4678 D(INFLATION) 0.356444 0.135140 2.637597 0.0335 D(INFLATION(-1)) -0.062594 0.178949 -0.349790 0.7368 D(INFLATION(-2)) -0.826226 0.193346 -4.273312 0.0037 D(INFLATION(-3)) 0.480229 0.146283 3.282870 0.0134 Coint Eq(-1) -1.051122 0.236316 -4.447940 0.0030

Cointeq = PHCR - (-0.6186*GDPA + 0.4776*EXTGNI + 11.0851*FDIGDP +

17.3681*PGA -193.0466*RTOP + 0.6245*INFLATION + 17.6115 )

Long Run Coefficients

Variable Coefficient Std. Error t-Statistic Prob.

GDPA -0.618592 0.970315 -0.637516 0.5441

EXTGNI 0.477577 0.116112 4.113083 0.0045

FDIGDP -11.085096 4.596633 2.411569 0.0467

PGA 17.368126 10.034473 1.730846 0.1271

RTOP

-

193.046583 75.223369 -2.566311 0.0372 INFLATION 0.624508 0.181103 3.448349 0.0107

C 17.611487 8.252327 2.134124 0.0702

Source: Author’s estimations using E-Views software

To find the long relationship among globalization, poverty, FDI, gross domestic product percentage per annual, gross population percentage per annual, external debt and trade openness measured through (import+ export) ratio we used ARDL approach to interpret the empirical result because ARDL technique is used when all the variable is not stationary on level and some are on 1^st difference. Using the bound test, the result of Long run relationship of Null Hypothesis has rejected because the computed value of F statistics is highly significant. This explore that there is a long run relationship between globalization and poverty. The result defines that globalization has negative impact on poverty. One unit change in GDPA can brings decrease of Poverty head count ratio 0.61% and increase in external debt can bring 0.47% change in PHCR. One unit change in population growth can bring a 17%

change in PHCR, as we know growing population creates some serious problem.

Population growth per annual is positively related to poverty if population is increasing its means that expensive of Govt also increasing and people needs more basic facilities to meet the living standard of life. We measure the globalization by trade openness. In this regard we used calculated sum of ratio (import + export) for trade openness and we found that trade openness has negatively impact on poverty head count ratio in Pakistan. Increasing trade openness is the main cause of reducing poverty in Pakistan. One unit change in trade openness brings -193 changes in poverty. The average poverty in Pakistan has remained 25% to 30% during 1970 to 2016 while maximum poverty level 35% and minimum poverty level is 17% in Pakistan. Remittances and official development aid also reduce poverty. The standard deviation of poverty is around 3.5% and the average inflation remained 8% to 9%

during 1970 to 2016. Trade openness and GDPA has skewed the negative impact on poverty while GPA External debt and inflation has positive impact on poverty in Pakistan. While FDI is also showing the negative relationship between poverty. It means that increasing FDI is also playing a vital role in reducing poverty in Pakistan.

One unit increasing in FDI can brings a 0.11% change in poverty. R Squared value shows the significant of the study while µ is the stochastic term used for error. This result indicates that globalization has negative impact on poverty in Pakistan.

5. CONCLUSIONS:

We conclude that globalization has strong positive impact on poverty and economic growth and significantly reduced level of poverty in Pakistan. Increasing trade openness, FDI and GDP are the main dynamics for reducing poverty in Pakistan.

It means there is close association between globalization and poverty in the context of Pakistan. The gist of this study is that potential benefits and true gains of globalization are still to explored under GST+ system and for getting abolished quota system imposed by the United States and European Union.

6. POLICY RECOMMENDATIONS:

We would like to present the following recommendations for policy makers:

● If Pakistan wants to gain fruitful result and advantage of globalization, Pakistan dire needs to take some structural reforms and policies regarding trade openness imports exports and poverty at macro level.

● Pakistan should pay some serious attention to employment creation. Media and tourism can also play a vibrant role in generating employment.

● Pakistan should pay proper attention to improve law and order situation to attract international business community to invest in Pakistan.

● In 2015 European Union has given a GST+ plus status to Pakistan and sixty-five- time free trade agreement but Pakistan has not fully capitalized this status fully and is still has to realize its potential.

● Pakistan trade is still limited to specially two Sub continents Europe and America only in products and markets and still has to explore other market like central Asia Australia and Africa.

_________________________

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CONTRIBUTION OF AUTHORS AND CONFLICT OF INTEREST

This research work was carried between collaboration of two authors.

Author 1: Afroz Umair is an M.Phil scholar at Department of Economics, Institute of Southern Punjab. He designed the study, collected and analyzed data. He also wrote first draft of the manuscript under the supervision of author 2.

Author 2: Prof. Dr. Abdul Ghafoor Awan has his first Ph.Ds in Economics from Islamia University of Bahawalpur-Pakistan and second in Business Administration from University of Sunderland, U.K. He contributed in this research paper by way of guiding author first about title selection, data collection and statistical technique. He edited and gave final shape to the manuscript. In order to know about his fields of research please look at his Web of Science Researcher ID M-9196 2015 or his profile at Google scholar.

Both authors read the manuscript carefully and declared no conflict of interest with any person or institution.